Long-alkyl-chain alcohols are promising biofuel alternatives to fossil fuels; however, their detection has been a challenging task. In this study, the responses of nanoscale Pt-based sensors to aliphatic alcohols were examined, focusing on alkyl-chainlength and temperature dependencies. Atomistic simulations with a universal neural network potential were used to analyze the reaction and activation energies. Two types of Pt-based sensors were fabricated: a Pt nanosheet resistor sensor (PtNS) and a Pt nanoparticle-decorated graphene field-effect transistor sensor (PtNP-GFET). PtNP-GFET exhibited considerably higher sensor responses to 1-heptanol than to ethanol at 225 °C; moreover, PtNS showed the opposite alkyl-chain-length dependence compared to the response of PtNP-GFET at the same temperature. At a lower temperature of 150 °C, the sensor response toward ethanol and 1-heptanol in the case of PtNP-GFET was nearly identical, indicating that the response was primarily influenced by the concentration of hydroxyl groups. Atomistic simulation analysis revealed that the dehydrogenation reaction of the hydrocarbons near the hydroxyl groups was thermodynamically more favorable on the Pt 147 nanocluster than on the Pt(111) surface. The dehydrogenation from the alkyl chain by PtNP was confirmed in alkanes; this dehydrogenation caused a higher sensor response of PtNP-GFET to 1-heptanol than to ethanol at 225 °C. Overall, employing nanomaterials, namely nanostructured Pt catalysts and a graphene-FET transducer, and using multiple sensing temperatures are key factors for realizing long-alkyl-chain alcohol recognitions. A low temperature of 150 °C is suitable for hydroxyl group sensing, while a high temperature of 225 °C is preferable for hydrocarbon group sensing.